A fundamental operation in computer vision is to compare two pixels to determine whether they indicate a similar intensity value or a similar color value or the like. Accurate measurement and comparison of light intensity at a camera's pixels depends on the noise characteristics of the camera. Due to these noise characteristics, the measured values of the pixels in a digital image may fluctuate over some range around the actual intensity values. The characteristics of this fluctuation may vary from camera to camera, from pixel to pixel in the same camera, and even within the same pixel. Accordingly, measuring how similar two pixels are to each other must be done while considering the noise characteristics of a camera and their impact on the pixel values. Conventional similarity comparison techniques, such as L2 norm and the like, tend to be lacking with respect to the impact of camera noise characteristics on intensity.